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Heads of talent and HR leads ask AI assistants which ATS fits their hiring volume, team and tools. We work on what those answers say about your product, and whether they name it at all.
Updated
“Which ATS suits a 300-person company hiring 60 people a year, with a two-person talent team on Google Workspace?”
“Vendor A and Vendor B suit small talent teams on Google Workspace. Vendor C has deeper reporting but takes longer to set up…”
Placeholders, not real vendors or results.
Buyers type a few words into a search box. In an AI assistant they describe their situation: how many people they hire a year, the size of the talent team, the HR system they run, the roles they struggle to fill. Each detail narrows the shortlist, and each one is a fact the answer has to get right about you.
In a search box
In an AI assistant
Example questions, written to show the shape. Vendor names are placeholders.
The paid audit and every monthly check record how each engine describes you, not only whether it names you. For an ATS, these are the details a talent team compares.
Hiring volume, team size and the regions a company hires in. A team filling a few roles a quarter and one hiring every week need different workflows.
Scheduling, scorecards, offers, a careers page and reporting. Buyers ask whether they will need extra tools on top of you.
The HR system, job boards, calendars and assessment tools. Buyers check the list against what they already run.
Moving candidate history across and the time to go live. A buyer leaving another system asks about this early.
Privacy rules, equal opportunity reporting and retention. The answer has to state what you support today.
Engines that search the web show their sources. For your own questions, the baseline records which of these each engine used, so the work goes where your answers come from.
The same four steps run on every retainer. The plan you pick sets how many questions we track and how much work ships each term.
We build the questions heads of talent and HR leads ask, with you: 100 or 150 depending on the plan, mostly unbranded, grouped into clusters by hiring volume, feature and stage. You approve them before anything runs.
Every question runs on ChatGPT, Claude, Perplexity, Microsoft Copilot and Google (AI Overviews, AI Mode and Gemini). We record who gets named, how each engine describes who you suit and what's built in, and which pages it cites.
A written estimate of what the scope can move by day 90, as ranges per cluster and engine. The scope is locked with it.
Comparison and alternatives pages, revamps of product and comparison pages you already have, corrected review profiles, placements on the pages engines cite, and community work. Each month end is measured against the forecast.
If we work with one applicant tracking vendor, we don't take its direct competitor, so we are never chasing the same citations for two of you.
Nobody controls what the engines say. You get a measured baseline, a written forecast and a monthly check that shows a flat month as flat.
Talent leaders notice content written by someone who has never run a hiring process. We interview your product lead at the start, then for 30 minutes a month, and you approve every brief.
Example questions are illustrative.
It is how often, and how accurately, AI assistants such as ChatGPT, Claude, Perplexity, Microsoft Copilot and Google's AI features name your product when talent and HR leads ask which applicant tracking system fits their hiring. It covers being on the shortlist and being described correctly: who you suit, what's built in, what you connect to and how switching works.
Send your website, your category in a sentence and up to five competitors. If we think the free audit will tell you something, it arrives 48 business hours after we confirm.